Justifying the need for a recovery related surveillance system: Exploratory focused interviews

Abstract Background and Aims No recovery related surveillance system exists but given the evidence of effectiveness and growing supply, a house‐ and resident‐ level recovery house (RH) surveillance system could be beneficial for data collection on recovery support service (RSS) engagement, and retention; for improved standardization of RH programs and services; and for identification of outcomes associated with long‐term recovery. Methods This study aimed to explore current data collection practices at the resident‐ and house‐ level through qualitative focus interviews of RH representatives. The 13 RH interviews were scheduled with 16 RH representative respondents. Results The most frequently collected resident data was at entry (92%) and departure (85%) and included demographics (n = 5), substance use history (n = 6), treatment and recovery history (n = 5), legal and correctional history (n = 6) and mental health information (n = 7). Recovery support data was collected by 85% of houses. Post‐stay data was only collected by four RHs (31%). Conclusion These results indicate that there is a lack of standardized systematic collection, analysis, and reporting of recovery related data in the RH field. A recovery related surveillance system has the potential to fill this gap and inform and improve standard of resident care to support long‐term recovery from substance use disorder.

Public health surveillance is defined as "ongoing systematic collection, analysis, and interpretation of health-related data essential to planning, implementation, and evaluation of public health practice." 8rrently, no recovery related surveillance system exists but given the evidence of effectiveness and growing supply, a house-and residentlevel RH surveillance system could be beneficial for data collection on recovery support service (RSS) engagement, and retention; for improved standardization of RH programs and services; and for identification of outcomes associated with long-term recovery.This study aims to explore current data collection practices at the resident-and house-level through qualitative focus interviews of RH representatives.

| Interview guide development
A semi-structured interview guide was designed and reviewed by subject matter experts to gather comprehensive information about RH resident and house data collection, data reporting, and processes/ procedures.The study was approved by the University of Kentucky IRB #53931.

| Participant recruitment
A purposive sampling approach was employed; potential candidates were identified through the Rural Center of Excellence in Recovery.A recruitment email outlining the study was sent and candidates responsive were sent an invitation for a 1-h interview.Candidates unresponsive to the initial invitation were sent a reminder email after 2 weeks, and ~4 weeks.Data collection occurred in December 2020.

| Interview process
The 13 RH interviews were scheduled with 16 RH representative respondents and were randomly assigned to study team members.The RH respondents included RH executives, owners, managers, and other RH administrators.Consent was obtained before the interview.The meetings were recorded in, and automatically transcribed by Zoom.

| Code book development
A hybrid coding approach of inductive and deductive processes was employed. 9The deductive approach resulted in three categories of identified (Data Collection and Reporting, RH Processes and Procedures, and Website Recommendations) based on the interview questions.After codebook development, an inductive method was employed for codebook usability testing.The study team coded two transcripts each, searching for code utility and gaps.When code gaps were found, new codes were developed with group consensus.

| Interview data analysis
Intercoder reliability scores for were 0.87, calculated utilizing percent agreement between two interviews chosen at random and averaging scores.Interview coding was conducted in two rounds.In each round, two study team members independently coded each transcript in Microsoft Word then Excel was used to compile interview code data. 10The first round of coding also tested the codebook to ensure codes were comprehensive.No codebook edits were required after round one was completed.In round two, two study team members coded the same transcript independently.Once coding rounds were completed, an additional study team member input all codes into one Excel document and checked for coding discrepancies.Coding discrepancies were resolved by study team members.
All coded data was analyzed in Excel, and qualitative themes were identified.Some themes were re-organized to create subthemes. 11Identified themes included Mental Health, Recovery History, Medications, Manual Data Collection, and External Recipients of Reports.

| RESULTS
The 13 RHs participated; 38% were located in rural areas (based on Health Resources and Services Administration (HRSA) definition) and 62% were located in urban areas (HRSA, 2022).The 31% were located in Oregon, 15% in Montana, 15% in West Virginia, 15% in Kentucky, 8% in Idaho, 8% in Ohio, and 8% in Washington.
The most frequently collected resident data was at entry (92%) and departure (85%) and included demographics (n = 5), substance use history (n = 6), treatment and recovery history (n = 5), legal and correctional history (n = 6) and mental health information (n = 7) (Appendix 1).Recovery support data was collected by 85% of houses.

Post-stay data was only collected by four RHs (31%).
Forty-six percent indicated that resident progress was important to track; and 46% (n = 6) mentioned the importance of tracking recovery goals and RSS like social support, external program involvement, and job status.The majority (85%) collected RH program involvement and progress data; 73% collected this data digitally.One respondent that didn't collect data digitally stated: "I would love to have a technology piece to do that for me, instead of carrying around my shrewd notebook." The 11 houses (85%) collected RH financial information (Appendix 2); 77% (n = 10) collected data on resident rent.One respondent described using a pre-existing software system for tracking financial data.
Sixty-two percent reported RH data to external organizations; 54% reported to a public funder.Four RHs indicated having a system that could produce business related reports related to RH management would be beneficial to understand financials.For example, one respondent stated: "From a business perspective… the other metric that I think is important, that we track, but I think is just important in general is figuring out what your optimal revenue per month would be for the home.So, how much money could you feasibly take in if everyone paid in full on time versus the actual revenue that you're generat-ing… if you're losing money left and right at a certain point, you [have] to close down." Eleven RHs reported that having a system that could produce resident-level reports would be beneficial.Forty-six percent tracked room and bed availability digitally and 54% collected availability data manually.

| DISCUSSION
Results from this exploratory qualitative study with 13 RHs across seven states indicated that limited recovery resident data is regularly collected.
Regular collection and analysis of resident background information, SUD history, such as medication use, prior substance use and severity of use, and recovery capital has the potential to enhance in-house and local community RSS available to RH residents. 12Also, few RHs collected social support and other RSS data that are critical in assessing individuals' progress in initiating recovery. 12Additionally, regular collection and analysis of resident data has the potential to identify disparities by race, gender, and geographic location, 13  This study has limitations; it had a small sample size of 13 RHs, thus RH data provided by respondents may not be representative of the national landscape of RH data collection practices.There could be selection bias since this study did not include RHs without email capabilities.It is also possible that only interested RHs responded to the interview request.

| CONCLUSIONS
There is a lack of standardized systematic collection, analysis, and reporting of recovery related data in the RH field.A recovery related surveillance system has the potential to fill this gap and inform and improve standard of resident care to support long-term recovery from SUD.
and to inform development of tailored individualized RH programs and interventions.While most RHs collected resident entry and exit data, follow-up outcome data was rarely collected.A recovery related surveillance system with intake, departure, and longterm resident outcome data could examine RSSs associated with longterm SUD recovery; inform and improve RSS interventions; support outcomes informed recovery care; allow cost comparability of RH nationally; and to improve RH program quality and associated resident outcomes.